Digital Manufacturing • DM-01
AI Technical Monitoring
Catch equipment failure while it is still cheap to fix.
Scope
What the engagement covers.
Condition data usually exists but is only read after a breakdown. Technical monitoring turns vibration, temperature, current and process signals into early warnings with enough lead time to plan the intervention.
Included capabilities
- Continuous condition monitoring across rotating and static equipment
- Anomaly detection trained on the plant’s own normal operating envelope
- Remaining useful life estimation for critical asset classes
- Failure mode attribution linked to the maintenance catalogue
- Alert routing into the maintenance work order queue, not a separate screen
Outputs and deliverables
- Asset criticality and instrumentation plan
- Trained anomaly and failure models per asset class
- Alert-to-work-order integration
- Avoided-downtime tracking against baseline
Workflow
How it is delivered, step by step.
Each step has an owner, an entry condition and an artefact that has to exist before the next step begins.
01SelectCritical assets by downtime cost, failure history and data availability.
02InstrumentSensors, gateways and historian tags with quality validation.
03LearnBaseline normal behaviour across load, product and seasonal variation.
04AlertThresholds and models tuned to minimise false alarms.
05Close loopAlerts become work orders; outcomes feed model refinement.
Use cases
Where this is typically applied.
Assets under condition-based maintenance regulatory regimes
Plants reducing spare parts inventory through predictive planning
Delivery model
The operating pattern for Digital Manufacturing.
The same delivery discipline applies across every capability in this line, so combined engagements stay coherent.
Baseline
Asset register, data availability, loss analysis and value case per line.
Connect
Sensors, gateways, historians, protocol translation and network coverage.
Model
Twins, failure models, OEE logic and analytics validated against real events.
Deploy
Operator and maintainer workflows, alerts, dashboards and situation centre.
Scale
Second line, second site, standard templates and capability transfer.
Integration
- MES, APS, ERP and CMMS so insight becomes a work order, not a dashboard.
- SCADA, historians and PLC layers via standard industrial protocols.
- Quality and laboratory systems for genealogy and root-cause analysis.
- Private LTE/5G or industrial Wi-Fi for coverage in electrically noisy plants.
Engagement approach
Deployment starts on one line or one asset class where losses are measurable, so the business case is proven on real production data before the site-wide rollout is committed.
Related
Other capabilities in Digital Manufacturing.
DM-02
Digital Twin
A live model of the plant that answers questions before you commit to the change.
DM-03OEE / Asset Scoring
One honest number for equipment performance, built from data nobody can argue with.
DM-04Situation Center
One room where production, maintenance, quality and energy are looked at together.
DM-05AI Maintenance Assistant
Put twenty years of maintenance knowledge in the technician’s hand.
DM-06Robot Fleet Management
Treat robots and AGVs as a managed fleet, not as isolated machines.
DM-07MES / APS / SCADA-HMI Integration
Make the execution layer, the planner and the control layer agree.
DM-08Private LTE/5G & Industrial Connectivity
Coverage that survives metal, movement and electrical noise.
DM-09Smart Workshop
Digitize the workplaces where most variability actually originates.
DM-10Industrial Safety
Detect the unsafe condition before it becomes the incident report.
DM-11Environmental & Energy Management
Attribute energy and emissions to the process that actually consumed them.